|Current CSR Projects in Maritime Domain Awareness (MDA)|
This vessel detection research project develops new understanding and new processes for receiving and analyzing large maritime area data from multi-satellite and multi-frequency sensors such as Synthetic Aperture Radar (SAR) and electro-optical (EO) sensors. Algorithms will be developed to employ the data to detect vessels, including small ships, in harbors, the coastal ocean and the high seas. Algorithms are also being developed to integrate this vessel detection information with ground-based systems such as AIS.
HF Radar and Over-The-Horizon Surveillance
This research project's goal is to develop robust detection algorithms that recognize ship-associated HF Radar signals above the background noise (e.g., surface waves). Algorithms are being developed to support vessel detection and tracking capabilities using compact HF Radars, demonstrating that ships, including small ships, can be detected and tracked by multistatic HF Radar in a multi-ship environment while simultaneously mapping ocean currents.
Nearshore and Harbor Surveillance
Given the density of commercial and recreational vessel traffic in the nation's estuary and harbor environments, vessel detection, tracking, and classification of small ships (including surface and underwater) is essentially impossible given today's COTS and GOTS technologies. This project's goal is to examine the use of systems of sensors that can provide continuous, high-resolution, all-weather vessel detection surveillance of the vessel traffic in these environments. New and existing sensor technologies are examined, including underwater acoustic, video cameras, and IR cameras operating at different wavelengths. These sensors are coupled with advanced data integration, pattern recognition, anomaly detection, and decision-support systems.